-
Notifications
You must be signed in to change notification settings - Fork 7
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
[Segmentation] Add Segment Anything Model #132
Merged
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
…onal attention, etc
… partitioning and unpartitioning
…t multihead attention
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Adds Segment Anything model in three flavors:
deepvision.models.SAM_B
...SAM_H
)deepvision.models.PromptableSAM
)deepvision.models.SAMAutoMaskGenerator
)The SAM model is implemented in PyTorch only, however, most of the components are implemented in both PyTorch and TensorFlow. Components not implemented in TensorFlow are tracked in #129, #130 and #131.
The layers and classes that do expose both a PyTorch and TensorFlow implementation are:
deepvision.layers.WindowUnpartitioning
deepvision.layers.WindowPartitioning
deepvision.layers.DownscalingMultiheadAttention
deepvision.layers.TwoWayAttentionBlock
deepvision.layers.TwoWayTransformerDecoder
deepvision.layers.RelativePositionalTransformerEncoder
deepvision.layers.RelativePositionalMultiheadAttention
deepvision.layers.RandomPositionEmbedding
deepvision.layers.AddDecomposedRelativePositions
All layers have identical implementations and parameter counts.